Episode 85 — Evaluate identity and access management for AI models, data, and keys (Task 16)
This episode teaches you how to evaluate identity and access management for AI systems, because Task 16 scenarios often test whether you protect the most sensitive assets: models, training data, and the keys and tokens that enable inference and integrations. You’ll learn to map identities across humans, service accounts, automation, and vendor access, then verify that each role has only the permissions needed to perform approved tasks. We’ll cover why access is more complex in AI, including separate access paths for datasets, labeling tools, model registries, deployment pipelines, and inference endpoints, plus secrets management for API keys and signing keys. You’ll also learn what evidence auditors expect, such as role definitions, access reviews, approval records for privileged access, key rotation practices, and logs that show access and changes are monitored. By the end, you should be able to answer exam questions by choosing IAM controls that preserve integrity, confidentiality, and accountability across the AI lifecycle, not just at the application layer. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your educational path. Also, if you want to stay up to date with the latest news, visit DailyCyber.News for a newsletter you can use, and a daily podcast you can commute with.
